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6
Commits
| Author | SHA1 | Date | |
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cec2bc5ff6 | ||
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b7f69c2c1d | ||
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23a4531491 | ||
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7d52ad0118 | ||
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4d7bf35fa3 | ||
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a6a9c9ca07 |
@@ -106,6 +106,8 @@ If you encounter CUDA out of memory errors:
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- Enable memory optimization with `enable_model_cpu_offload`
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- Try a smaller model or use distilled versions
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- Use `num_gpus` > 1 if multiple GPUs are available
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- Try enabling FSDP inference with `use_fsdp_inference=True` (may slow down generation)
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- Try enabling DiT layerwise offload with `dit_layerwise_offload=True` (now only a few models support this, but may introduce less overhead than FSDP)
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### Slow Generation
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@@ -12,7 +12,7 @@ def main():
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"Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=False,
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -14,7 +14,7 @@ def main():
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model_name,
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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# Adjust these offload parameters if you have < 32GB of VRAM
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text_encoder_cpu_offload=True,
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pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
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@@ -12,7 +12,7 @@ def main():
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"hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True,
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vae_cpu_offload=True,
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text_encoder_cpu_offload=True,
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@@ -55,7 +55,7 @@ def basic_generation():
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generator = VideoGenerator.from_pretrained(
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"FastVideo/LongCat-Video-I2V-Diffusers",
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=False,
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vae_cpu_offload=True,
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text_encoder_cpu_offload=True,
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@@ -48,7 +48,7 @@ def basic_generation():
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generator = VideoGenerator.from_pretrained(
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"FastVideo/LongCat-Video-T2V-Diffusers",
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=False,
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vae_cpu_offload=True,
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text_encoder_cpu_offload=True,
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@@ -66,7 +66,7 @@ def basic_generation():
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generator = VideoGenerator.from_pretrained(
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"FastVideo/LongCat-Video-VC-Diffusers",
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=False,
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vae_cpu_offload=True,
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text_encoder_cpu_offload=True,
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@@ -43,7 +43,7 @@ def main():
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config["model_path"],
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -46,7 +46,7 @@ async def main():
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config["model_path"],
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -13,7 +13,7 @@ def main():
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model_name,
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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text_encoder_cpu_offload=False,
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dit_cpu_offload=False,
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)
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@@ -14,7 +14,7 @@ def main():
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"FastVideo/SFWan2.2-I2V-A14B-Preview-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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dit_precision="fp32",
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vae_cpu_offload=False,
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@@ -14,7 +14,7 @@ def main():
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"rand0nmr/SFWan2.2-T2V-A14B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -15,6 +15,7 @@ def main() -> None:
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"loayrashid/TurboWan2.1-T2V-1.3B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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# set to false if using RTX 4090
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# pin_cpu_memory=False,
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@@ -12,7 +12,7 @@ def main():
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"Wan-AI/Wan2.2-T2V-A14B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -14,7 +14,7 @@ def main():
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# "alibaba-pai/Wan2.2-Fun-A14B-Control",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -12,7 +12,7 @@ def main():
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"Wan-AI/Wan2.2-I2V-A14B-Diffusers",
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -11,7 +11,7 @@ def main():
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model_name,
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True,
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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@@ -132,7 +132,7 @@ class FastVideoArgs:
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# CPU offload parameters
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dit_cpu_offload: bool = True
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use_fsdp_inference: bool = True
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use_fsdp_inference: bool = False
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dit_layerwise_offload: bool = False
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text_encoder_cpu_offload: bool = True
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image_encoder_cpu_offload: bool = True
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@@ -431,7 +431,9 @@ class FastVideoArgs:
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"--use-fsdp-inference",
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action=StoreBoolean,
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help=
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"Use FSDP for inference by sharding the model weights. Latency is very low due to prefetch--enable if run out of memory.",
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"Use FSDP for inference by sharding the model weights. FSDP helps reduce GPU memory usage but may introduce"
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+
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" weight transfer overhead depending on the specific setup. Enable if run out of memory.",
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)
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parser.add_argument(
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"--text-encoder-cpu-offload",
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BIN
Binary file not shown.
@@ -161,7 +161,7 @@ def test_turbodiffusion_inference_similarity(prompt, model_id):
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# TurboDiffusion I2V parameters (dual-model with RCM scheduler + SLA attention)
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TURBODIFFUSION_I2V_PARAMS = {
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"num_gpus": 2,
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"num_gpus": 4,
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"model_path": "loayrashid/TurboWan2.2-I2V-A14B-Diffusers",
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"height": 480,
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"width": 832,
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@@ -169,7 +169,7 @@ TURBODIFFUSION_I2V_PARAMS = {
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"num_inference_steps": 4, # TurboDiffusion uses 1-4 steps
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"guidance_scale": 1.0, # No CFG for TurboDiffusion
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"seed": 42,
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"sp_size": 2,
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"sp_size": 4,
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"tp_size": 1,
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"fps": 24,
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}
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@@ -218,6 +218,8 @@ def test_turbodiffusion_i2v_inference_similarity(prompt, model_id):
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"sp_size": BASE_PARAMS["sp_size"],
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"tp_size": BASE_PARAMS["tp_size"],
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"override_pipeline_cls_name": "TurboDiffusionI2VPipeline",
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# Keep both transformers in VRAM - avoids CPU RAM bottleneck
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"dit_cpu_offload": False,
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}
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generation_kwargs = {
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+1
-1
@@ -111,7 +111,7 @@ lint = [
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]
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test = [
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"av==14.3.0",
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"av",
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"pytorch-msssim==1.0.0",
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"pytest",
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]
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@@ -90,7 +90,7 @@ lint = [
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]
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test = [
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"av==14.3.0",
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"av",
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"pytorch-msssim==1.0.0",
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"pytest",
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]
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Reference in New Issue
Block a user